The present invention generally relates to an image coding apparatus, an image coding method, an image decoding apparatus, and a recording medium. More specifically, the present invention is directed to image coding method/apparatus capable of compressing/coding component image signals in a high efficiency, and also to an image decoding apparatus and a recording medium.
Conventionally, various methods of compressing images have been proposed. The ADRC (Adaptive Dynamic Range Coding) method is known as one of these image compressing methods.
This ADRC method will now be described. For the sake of a simple explanation, as indicated in FIG. 1A, considering now such a block constituted by four pixels arranged on a straight line in this ADRC method, a maximum value "MAX" and a minimum value "MIN" of the pixel values within this block are first detected. Then, while DR=MAX-MIN is set as the localized dynamic range of the block, the pixel values of the pixels for constituting the block are requantized into the K bits based upon this dynamic range DR.
In other words, the minimum value MIN is subtracted from each of the pixel values within the block, and this subtraction value is divided by DR/2.sup.K. Then, as a result, the minimum value is converted into the code (ADRC code) corresponding to the resultant division value. Concretely speaking, for instance, in the case of K=2, as represented in FIG. 1B, a judgment is made as to whether or not the division value belongs to any of the ranges obtained by equally dividing the dynamic range DR by 4 (=2.sup.2). In the case that the division value belongs to the lowermost level range, the second lowermost level range, the third lowermost level range, or the uppermost level range, the respective division values are converted into 2-bit codes such as 00B, 01B, 10B, 11B (symbol "B" indicates binary number). Then, in the decoding operation, the ADRC code 00B, 01B, 10B, or 11B is converted into the center value (level) L.sub.00, of the lowermost level range, the center value L.sub.01, of the second lowermost level range, the center value L.sub.10 of the third lowermost level range, or the center value L.sub.11 of the uppermost level range, which are obtained by equally dividing the dynamic range DR by 4. Then, the minimum value MIN is added to the converted value, so that the decoding operation is carried out.
In this case, such an ADRC processing is referred to as "non-edge matching". In contrast to this non-edge matching, as indicated in FIG. 1C, another ADRC processing has been proposed which is referred to as "edge matching". That is, in this edge matching, either the ADRC code 00B or the ADRC code 11B is converted into the average value MIN' of the pixel values belonging to the lowermost level range obtained by equally dividing the dynamic range DR by 4, or the average value MAX' of the pixel values belonging to the uppermost level range, respectively. Furthermore, both the ADRC codes 01B and 10B are converted into such a level for equally dividing the dynamic range DR' by 3, which is defined by MAX'-MIN', so that the ADRC codes are decoded.
It should be noted that the ADRC processing operation is disclosed more in detail, for instance, in Unexamined Published Japanese Patent Application No. Hei 3-53778 previously filed by the Applicant.
In accordance with the ADRC processing operation, the requantization is carried out based on the bit number smaller than the bit number allocated to the respective pixels for constituting the block, so that the data amount of the image can be reduced.
On the other hand, an image signal may be mainly classified into, for instance, a composite signal of the NTSC system or the PAL system, and a component signal of RGB, YUV, YIQ, CMY(K), depending upon the sort of this image signal.
As to an image constructed of composite signals, the coding process operation may be carried out only for the composite signals. However, as to an image constructed of component signals, the coding process operation must be carried out for each of three components, namely R, G, B components, or Y, U, V components, or Y, I, Q components, which constitute the component signal.
As a result, simply comparing two different types of images, the produced coding amount obtained by coding the image constructed of the component signals becomes three times larger than that obtained by coding the image constructed of the composite signals.